Cooperating elephants mitigate competition until the stakes get too high

Cooperation is ubiquitous in the animal kingdom as it aims to maximize benefits through joint action. Selection, however, may also favor competitive behaviors that could violate cooperation. How animals mitigate competition is hotly debated, with particular interest in primates and little attention paid thus far to nonprimates. Using a loose-string pulling apparatus, we explored cooperative and competitive behavior, as well as mitigation of the latter, in semi-wild Asian elephants (Elephas maximus). Our results showed that elephants first maintained a very high cooperation rate (average = 80.8% across 45 sessions). Elephants applied “block,” “fight back,” “leave,” “move side,” and “submission” as mitigation strategies and adjusted these strategies according to their affiliation and rank difference with competition initiators. They usually applied a “fight back” mitigation strategy as a sanction when competition initiators were low ranking or when they had a close affiliation, but were submissive if the initiators were high ranking or when they were not closely affiliated. However, when the food reward was limited, the costly competitive behaviors (“monopoly” and “fight”) increased significantly, leading to a rapid breakdown in cooperation. The instability of elephant cooperation as a result of benefit reduction mirrors that of human society, suggesting that similar fundamental principles may underlie the evolution of cooperation across species.

This study shows that in a task requiring coordinated pulling, elephants compete for access to food but work to mitigate competition in order to maintain cooperation. If the cost of competition becomes too high, however, cooperation breaks down entirely. This behavior mirrors that seen in humans and other great apes, suggesting that certain cooperative mechanisms are not unique to primates.     

Quilt Plots: A Simple Tool for the Visualisation of Large Epidemiological Data

Background

Graphical representation of data is one of the most easily comprehended forms of explanation. The current study describes a simple visualization tool which may allow greater understanding of medical and epidemiological data.

Method

We propose a simple tool for visualization of data, known as a “quilt plot”, that provides an alternative to presenting large volumes of data as frequency tables. Data from the Australian Needle and Syringe Program survey are used to illustrate “quilt plots”.

Conclusion

Visualization of large volumes of data using “quilt plots” enhances interpretation of medical and epidemiological data. Such intuitive presentations are particularly useful for the rapid assessment of problems in the data which cannot be readily identified by manual review. We recommend that, where possible, “quilt plots” be used along with traditional quantitative assessments of the data as an explanatory data analysis tool.     

Fuzzy Nonlinear Proximal Support Vector Machine for Land Extraction Based on Remote Sensing Image

Currently, remote sensing technologies were widely employed in the dynamic monitoring of the land. This paper presented an algorithm named fuzzy nonlinear proximal support vector machine (FNPSVM) by basing on ETM⁺ remote sensing image. This algorithm is applied to extract various types of lands of the city Da’an in northern China. Two multi-category strategies, namely “one-against-one” and “one-against-rest” for this algorithm were described in detail and then compared. A fuzzy membership function was presented to reduce the effects of noises or outliers on the data samples. The approaches of feature extraction, feature selection, and several key parameter settings were also given. Numerous experiments were carried out to evaluate its performances including various accuracies (overall accuracies and kappa coefficient), stability, training speed, and classification speed. The FNPSVM classifier was compared to the other three classifiers including the maximum likelihood classifier (MLC), back propagation neural network (BPN), and the proximal support vector machine (PSVM) under different training conditions. The impacts of the selection of training samples, testing samples and features on the four classifiers were also evaluated in these experiments.     

Money Walks: Implicit Mobility Behavior and Financial Well-Being

Traditional financial decision systems (e.g. credit) had to rely on explicit individual traits like age, gender, job type, and marital status, while being oblivious to spatio-temporal mobility or the habits of the individual involved. Emerging trends in geo-aware and mobile payment systems, and the resulting “big data,” present an opportunity to study human consumption patterns across space and time. Taking inspiration from animal behavior studies that have reported significant interconnections between animal spatio-temporal “foraging” behavior and their life outcomes, we analyzed a corpus of hundreds of thousands of human economic transactions and found that financial outcomes for individuals are intricately linked with their spatio-temporal traits like exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models.     

A Web-based semantic tagging and activity recognition system for species' accelerometry data

Increasingly, animal biologists are taking advantage of low cost micro-sensor technology, by deploying accelerometers to monitor the behavior and movement of a broad range of species. The result is an avalanche of complex tri-axial accelerometer data streams that capture observations and measurements of a wide range of animal body motion and posture parameters. Analysis of these parameters enables the identification of specific animal behaviors—however the analysis process is immature with much of the activity identification steps undertaken manually and subjectively. Consequently, there is an urgent need for the development of new tools to streamline the management, analysis, indexing, querying and visualization of such data. In this paper, we present a Semantic Annotation and Activity Recognition (SAAR) system which supports storing, visualizing, annotating and automatic recognition of tri-axial accelerometer data streams by integrating semantic annotation and visualization services with Support Vector Machine (SVM) techniques. The interactive Web interface enables biologists to visualize and correlate 3D accelerometer data streams with associated video streams. It also enables domain experts to accurately annotate or tag segments of tri-axial accelerometer data streams, with standardized terms from an activity ontology. These annotated data streams can then be used to dynamically train a hierarchical SVM activity classification model, which can be applied to new accelerometer data streams to automatically recognize specific activities. This paper describes the design, implementation and functional details of the SAAR system and the results of the evaluation experiments that assess the performance, usability and efficiency of the system. The evaluation results indicate that the SAAR system enables ecologists with little knowledge of machine learning techniques to collaboratively build classification models with high levels of accuracy, sensitivity, precision and specificity.     

Networks of Causal Linkage Between Eigenmodes Characterize Behavioral Dynamics of Caenorhabditis elegans

Behavioral phenotyping of model organisms has played an important role in unravelling the complexities of animal behavior. Techniques for classifying behavior often rely on easily identified changes in posture and motion. However, such approaches are likely to miss complex behaviors that cannot be readily distinguished by eye (e.g., behaviors produced by high dimensional dynamics). To explore this issue, we focus on the model organism Caenorhabditis elegans, where behaviors have been extensively recorded and classified. Using a dynamical systems lens, we identify high dimensional, nonlinear causal relationships between four basic shapes that describe worm motion (eigenmodes, also called “eigenworms”). We find relationships between all pairs of eigenmodes, but the timescales of the interactions vary between pairs and across individuals. Using these varying timescales, we create “interaction profiles” to represent an individual’s behavioral dynamics. As desired, these profiles are able to distinguish well-known behavioral states: i.e., the profiles for foraging individuals are distinct from those of individuals exhibiting an escape response. More importantly, we find that interaction profiles can distinguish high dimensional behaviors among divergent mutant strains that were previously classified as phenotypically similar. Specifically, we find it is able to detect phenotypic behavioral differences not previously identified in strains related to dysfunction of hermaphrodite-specific neurons.     

Collective predator evasion: Putting the criticality hypothesis to the test

According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the “criticality hypothesis”, appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the “criticality hypothesis”, but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality.     

Can Ethograms Be Automatically Generated Using Body Acceleration Data from Free-Ranging Birds?

An ethogram is a catalogue of discrete behaviors typically employed by a species. Traditionally animal behavior has been recorded by observing study individuals directly. However, this approach is difficult, often impossible, in the case of behaviors which occur in remote areas and/or at great depth or altitude. The recent development of increasingly sophisticated, animal-borne data loggers, has started to overcome this problem. Accelerometers are particularly useful in this respect because they can record the dynamic motion of a body in e.g. flight, walking, or swimming. However, classifying behavior using body acceleration characteristics typically requires prior knowledge of the behavior of free-ranging animals. Here, we demonstrate an automated procedure to categorize behavior from body acceleration, together with the release of a user-friendly computer application, “Ethographer”. We evaluated its performance using longitudinal acceleration data collected from a foot-propelled diving seabird, the European shag, Phalacrocorax aristotelis. The time series data were converted into a spectrum by continuous wavelet transformation. Then, each second of the spectrum was categorized into one of 20 behavior groups by unsupervised cluster analysis, using k-means methods. The typical behaviors extracted were characterized by the periodicities of body acceleration. Each categorized behavior was assumed to correspond to when the bird was on land, in flight, on the sea surface, diving and so on. The behaviors classified by the procedures accorded well with those independently defined from depth profiles. Because our approach is performed by unsupervised computation of the data, it has the potential to detect previously unknown types of behavior and unknown sequences of some behaviors.     

Differences in Behavior and Activity Associated with a Poly(A) Expansion in the Dopamine Transporter in Belgian Malinois

In Belgian Malinois dogs, a 38-base pair variable number tandem repeat in the dopamine transporter gene (SLC6A3) is associated with behavior changes in Malinois. By additional sequencing in SLC6A3, we identified an intronic 12-nucleotide poly(A) insertion (“PolyA(22)”) before the terminal exon that was associated with seizure, “glazing over” behaviors, and episodic biting behaviors in a sample of 138 Malinois. We next investigated whether PolyA(22) was associated with 1) increased locomotor activity and 2) response to novelty. Using a sample of 22 Malinois and 25 dogs of other breeds, dogs’ activity was monitored in a novel and non-novel environment while wearing activity monitoring collars. All dogs were more active in novel compared with non-novel environments, and Malinois were more active overall than other breeds. There was an effect of PolyA(22) genotype on activity levels, and this effect appeared to underlie the difference detected between Malinois and other breeds. There was no effect of PolyA(22) genotype on the relative decrease in activity between novel and non-novel environments for either group or all dogs considered together. In addition to an association between PolyA(22) and owner reports of seizure, “glazing over” behaviors, and episodic biting behaviors, these findings support an effect of PolyA(22) on dopamine transporter function related to activity. Further investigation is required to confirm mechanistic effects of PolyA(22) on SLC6A3. The complex polygenic nature of behavior and the range of behaviors associated with this insertion predict that effects are likely also modified by additional genetic and environmental factors.     

"Direct DICOM Slice Landmarking” A Novel Research Technique to Quantify Skeletal Changes in Orthognathic Surgery

The limitations of the current methods of quantifying the surgical movements of facial bones inspired this study. The aim of this study was the assessment of the accuracy and reproducibility of directly landmarking of 3D DICOM images (Digital Imaging and Communications in Medicine) to quantify the changes in the jaw bones following surgery. The study was carried out on plastic skull to simulate the surgical movements of the jaw bones. Cone beam CT scans were taken at 3mm, 6mm, and 9mm maxillary advancement; together with a 2mm, 4mm, 6mm and 8mm “down graft” which in total generated 12 different positions of the maxilla for the analysis. The movements of the maxilla were calculated using two methods, the standard approach where distances between surface landmarks on the jaw bones were measured and the novel approach where measurements were taken directly from the internal structures of the corresponding 3D DICOME slices. A one sample t-test showed that there was no statistically significant difference between the two methods of measurements for the y and z directions, however, the x direction showed a significant difference. The mean difference between the two absolute measurements were 0.34±0.20mm, 0.22±0.16mm, 0.18±0.13mm in the y, z and x directions respectively. In conclusion, the direct landmarking of 3D DICOM image slices is a reliable, reproducible and informative method for assessment of the 3D skeletal changes. The method has a clear clinical application which includes the analysis of the jaw movements “orthognathic surgery” for the correction of facial deformities.     

Self-Management Behavior in Patients with Type 2 Diabetes: A Cross-Sectional Survey in Western Urban China

Purpose

To investigate the current status of diabetic self-management behavior and the factors influencing this behavior in Chengdu, a typical city in western China.

Methods

We performed stratified sampling in 6 urban districts of Chengdu. We used questionnaires concerning self-management knowledge, self-management beliefs, self-management efficacy, social support, and self-management behavior to investigate patients with T2DM from August to November 2011. All of the data were analyzed using the SPSS 17.0 statistical package.

Results

We enrolled a total of 364 patients in the present study. The median score of self-management behavior was 111.00, the interquartile range was 100.00–119.00, and the index score was 77.77. Self-management was described as “good” in 46%, “fair” in 45%, and “poor” in 6% of patients. A multiple-factor analysis identified age (OR, 0.43; 95% CI, 0.20–0.91; P = 0.026), education in “foot care” (OR, 0.42; 95% CI, 0.18–0.99; P = 0.048), self-management knowledge (OR, 0.86; 95% CI, 0.80–0.92; P<0.001), self-management belief (OR, 0.92; 95% CI, 0.87–0.97; P = 0.002), self-efficacy (OR, 0.93; 95% CI, 0.90–0.96; P<0.001), and social support (OR, 0.62; 95% CI, 0.41–0.94; P = 0.023) as positive factors. Negative factors included diabetes duration (5–9 years: OR, 14.82; 95% CI, 1.64–133.73; P = 0.016; and ≥10 years: OR, 10.28; 95% CI, 1.06–99.79; P = 0.045) and hospitalization experience (OR, 2.96; 95% CI, 1.64–5.36; P<0.001).

Conclusion

We observed good self-management behavior in patients with T2DM in Chengdu. When self-management education is provided, age, education, knowledge, belief, self-efficacy, and social support should be considered to offer more appropriate intervention and to improve patients'' behavior.     

Discrimination of Complex Human Behavior by Pigeons (Columba livia) and Humans

The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors (“martial arts” vs. “Indian dance”). Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species.     

The Efficacy of Hyperbaric Oxygen Therapy on Middle Cerebral Artery Occlusion in Animal Studies: A Meta-Analysis

Background

Inconsistent results have been reported for hyperbaric oxygen therapy (HBO) for acute stroke. We conducted a systematic review and meta-analysis to evaluate the benefit of HBO in animal studies of middle cerebral artery occlusion (MCAO).

Methods

A systematic search of the literature published prior to September 2015 was performed using Embase, Medline (OvidSP), Web of Science and PubMed. Keywords included “hyperoxia” OR “hyperbaric oxygen” OR “HBO” AND “isch(a)emia” OR “focal cerebral ischemia” OR “stroke” OR “infarct” OR “middle cerebral artery occlusion (MCAO).” The primary endpoints were the infarct size and/or neurological outcome score evaluated after HBO treatment in MCAO. Heterogeneity was analyzed using Cochrane Library’s RevMan 5.3.5.

Results

Fifty-one studies that met the inclusion criteria were identified among the 1198 studies examined. When compared with control group data, HBO therapy resulted in infarct size reduction or improved neurological function (32% decrease in infarct size; 95% confidence interval (CI), range 28%–37%; p < 0.00001). Mortality was 18.4% in the HBO group and 26.7% in the control group (RR 0.72, 95% CI, 0.54–0.98; p = 0.03). Subgroup analysis showed that a maximal neuro-protective effect was reached when HBO was administered immediately after MCAO with an absolute atmospheric pressure (ATA) of 2.0 (50% decrease; 95% CI, 43% -57% decrease; p < 0.0001) and more than 6 hours HBO treatment (53% decrease; 95% CI, 41% -64% decrease; p = 0.0005).

Conclusions

HBO had a neuro-protective effect and improved survival in animal models of MCAO, especially in animals given more than 6 hours of HBO and when given immediately after MCAO with 2.0 ATA.     

Spontaneous Behaviors and Wall-Curvature Lead to Apparent Wall Preference in Planarian

The planarian Dugesia japonica tends to stay near the walls of its breeding containers and experimental dishes in the laboratory, a phenomenon called “wall preference”. This behavior is thought to be important for environmental adaptation, such as hiding by planarians in nature. However, the mechanisms regulating wall-preference behavior are not well understood, since this behavior occurs in the absence of any particular stimulation. Here we show the mechanisms of wall-preference behavior. Surprisingly, planarian wall-preference behavior was also shown even by the head alone and by headless planarians. These results indicate that planarian “wall-preference” behavior only appears to be a “preference” behavior, and is actually an outcome of spontaneous behaviors, rather than of brain function. We found that in the absence of environmental cues planarians moved basically straight ahead until they reached a wall, and that after reaching a wall, they changed their direction of movement to one tangential to the wall, suggesting that this spontaneous behavior may play a critical role in the wall preference. When we tested another spontaneous behavior, the wigwag movement of the planarian head, using computer simulation with various wigwag angles and wigwag intervals, large wigwag angle and short wigwag interval reduced wall-preference behavior. This indicated that wigwag movement may determine the probability of staying near the wall or leaving the wall. Furthermore, in accord with this simulation, when we tested planarian wall-preference behavior using several assay fields with different curvature of the wall, we found that concavity and sharp curvature of walls negatively impacted wall preference by affecting the permissible angle of the wigwag movement. Together, these results indicate that planarian wall preference may be involuntarily caused by the combination of two spontaneous planarian behaviors: moving straight ahead until reaching a wall and then moving along it in the absence of environmental cues, and wigwag movements of the head.     

Informing the Historical Record of Experimental Nonhuman Primate Infections with Ebola Virus: Genomic Characterization of USAMRIID Ebola Virus/H.sapiens-tc/COD/1995/Kikwit-9510621 Challenge Stock “R4368” and Its Replacement “R4415”

The creation of licensed medical countermeasures against Select Agents such as Ebola virus (EBOV) is critically dependent on the use of standardized reagents, assays, and animal models. We performed full genome reconstruction, population genomics, contaminant analysis, and characterization of the glycoprotein gene editing site of historical United States Army Medical Research Institute of Infectious Diseases (USAMRIID) nonhuman-primate challenge stock Ebola virus Kikwit “R4368” and its 2014 replacement “R4415.” We also provide characterization of the master stock used to create “R4415.” The obtained data are essential to understanding the quality of the seed stock reagents used in pivotal animal studies that have been used to inform medical countermeasure development. Furthermore, these data might add to the understanding of the influence of EBOV variant populations on pathogenesis and disease outcome and inform attempts to avoid the evolution of EBOV escape mutants in response to current therapeutics. Finally, as the primary challenge stocks have changed over time, these data will provide a baseline for understanding and correlating past and future animal study results.     

Evolutionary Establishment of Moral and Double Moral Standards through Spatial Interactions

Situations where individuals have to contribute to joint efforts or share scarce resources are ubiquitous. Yet, without proper mechanisms to ensure cooperation, the evolutionary pressure to maximize individual success tends to create a tragedy of the commons (such as over-fishing or the destruction of our environment). This contribution addresses a number of related puzzles of human behavior with an evolutionary game theoretical approach as it has been successfully used to explain the behavior of other biological species many times, from bacteria to vertebrates. Our agent-based model distinguishes individuals applying four different behavioral strategies: non-cooperative individuals (“defectors”), cooperative individuals abstaining from punishment efforts (called “cooperators” or “second-order free-riders”), cooperators who punish non-cooperative behavior (“moralists”), and defectors, who punish other defectors despite being non-cooperative themselves (“immoralists”). By considering spatial interactions with neighboring individuals, our model reveals several interesting effects: First, moralists can fully eliminate cooperators. This spreading of punishing behavior requires a segregation of behavioral strategies and solves the “second-order free-rider problem”. Second, the system behavior changes its character significantly even after very long times (“who laughs last laughs best effect”). Third, the presence of a number of defectors can largely accelerate the victory of moralists over non-punishing cooperators. Fourth, in order to succeed, moralists may profit from immoralists in a way that appears like an “unholy collaboration”. Our findings suggest that the consideration of punishment strategies allows one to understand the establishment and spreading of “moral behavior” by means of game-theoretical concepts. This demonstrates that quantitative biological modeling approaches are powerful even in domains that have been addressed with non-mathematical concepts so far. The complex dynamics of certain social behaviors become understandable as the result of an evolutionary competition between different behavioral strategies.     

Animal‐borne video systems provide insight into the reproductive behavior of the Asian black bear

Previous studies on the mating system of the Asian black bear (Ursus thibetanus) have been limited to observations of captive populations and estimations of multiple paternities. Hence, the mating system of wild bears remains poorly understood. Animal‐borne camera systems (i.e., cameras mounted on animals) provide novel tools to study the behavior of elusive animals. Here, we used an animal‐borne video system to record the activities of wild bears during the mating season. Video camera collars were attached to four adult Asian black bears (male “A” and “B,” and female “A” and “B”) captured in Tokyo, central Japan, in May and June 2018. The collars were retrieved in July 2018, after which the video data were downloaded and analyzed in terms of bear activity and mating behavior. All the bears were found to interact with other uniquely identifiable bears for some of the time (range 9–22 days) during the deployment period (range 36–45 days), and multiple mating in males was documented. Both males and females exhibited different behaviors on social days (i.e., days when the bear interacted with conspecifics) compared with solitary days (i.e., days with no observed interactions with conspecifics). Compared with solitary days, the bears spent a lower proportion of time on foraging activities and higher proportion of time on resting activities on social days. Our results suggest that Asian black bears have a polygamous mating system, as both sexes consort and potentially mate with multiple partners during a given mating season. Furthermore, bears appeared to reduce their foraging activities on social days and engaged more in social interactions.